Background Cardiometabolic diseases (CMDs) and chronic kidney disease (CKD) are closely interrelated in terms of disease risk and clinical outcomes. Estimated glomerular filtration rate (eGFR), a key indicator of renal function, is useful for the early identification and intervention of CKD. However, existing studies have mainly focused on the association between a single CMD, or its risk factors, and CKD. The impact of the coexistence of multiple CMDs, a common clinical phenomenon, on renal function remains insufficiently explored, particularly with regard to the differential effects of the number of comorbid conditions and specific disease combination patterns.
Objective To investigate the associations of cardiometabolic multimorbidity (CMM), the number of CMDs, and specific CMD combination patterns with eGFR, thereby providing evidence for the early identification and intervention of CKD.
Methods Data were obtained from the Early Screening and Comprehensive Intervention Program for High-risk Populations of Cardiovascular Disease in Anhui Province. From 2017 to 2022, community-dwelling residents from 12 cities in Anhui Province, including Suzhou, were surveyed. General demographic characteristics and biochemical indicators were collected. A total of 5 707 individuals aged 35-75 years at high risk of cardiovascular disease were ultimately included. eGFR was calculated using the CKD-EPI equation to assess renal function. Participants with eGFR≥90 mL·min-1·(1.73 m2)-1 and those with eGFR <90 mL·min-1·(1.73 m2)-1 were classified into the normal eGFR group (n=3 707) and abnormal eGFR group (n=2 000), respectively. Binary Logistic regression was used to evaluate the association between CMM and eGFR. The effects of the cumulative number of CMDs, stepwise increases in CMD number, and different CMM combination patterns on eGFR were further explored.
Results The prevalence of CMM in the study population was 51.3%. Binary Logistic regression analysis showed that, after adjustment for age, sex, marital status, education below high school level, annual household income <50 000 RMB, farming occupation, smoking, alcohol consumption, body mass index, and blood urea nitrogen, patients with CMM had a 1.28-fold higher risk of abnormal eGFR than those without CMM (OR=1.280, 95%CI=1.140-1.438, P<0.001). With an increasing number of CMDs, the risks of abnormal eGFR were as follows: two CMDs, OR=1.428, 95%CI=1.132-1.802, P=0.003; three CMDs, OR=1.465, 95%CI=1.126-1.905, P=0.004; and four CMDs, OR=2.352, 95%CI=1.570-3.524, P<0.001. A dose-response relationship was observed between the increasing number of CMDs and abnormal eGFR (OR=1.170, 95%CI=1.098-1.247, P<0.001). Compared with individuals without CMM, defined as having 0-1 CMD, those with two CMDs had a 24% increased risk of abnormal eGFR (OR=1.240, 95%CI=1.091-1.409, P<0.001). When the number of CMDs increased to three, no statistically significant difference was observed compared with two CMDs (OR=1.025, 95%CI=0.855-1.230, P=0.789). Compared with individuals with three CMDs, those with four or more CMDs had a 60.5% increased risk of abnormal eGFR (OR=1.605, 95%CI=1.102-2.337, P=0.014). Among participants with two, three, and four CMDs, the combinations associated with the greatest impact on eGFR were hypertension plus heart disease (OR=2.245, 95%CI=1.589-3.172, P<0.001), hypertension plus diabetes plus heart disease (OR=2.269, 95%CI=1.380-3.728, P=0.001), and hypertension plus diabetes plus dyslipidemia plus stroke (OR=2.645, 95%CI=1.997-3.713, P=0.021), respectively.
Conclusion CMM, as well as the number and combination patterns of CMDs, is closely associated with the risk of abnormal eGFR. These findings suggest that targeted screening and comprehensive management should be prioritized for individuals with four or more CMDs, while preventing the progression from two or three CMDs to four or more CMDs. In addition, attention to specific CMD combination patterns may represent an effective strategy for preventing CKD and improving prognosis.
